Automatic item categorizer

ABSTRACT

A categorization service is described that automatically categorizes items of interest to a user. The user may possess an item that they wish to offer for sale using the network-based service. The user may prepare an electronic description of the item and submit this item information to a categorization service for categorization. Upon receipt, the categorization service may compare the item information to item category descriptions representing item categories of the network-based server in order to determine category recommendations for the item of interest. The recommended categories are returned to the user to enable the user to assign a category, selected from the category recommendations, to the item of interest.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.12/605,260, entitled AUTOMATIC ITEM CATEGORIZER, and filed Oct. 23,2009, the entirety of which is incorporated herein by reference.

BACKGROUND

Generally described, computing devices and communication networksfacilitate network-based commerce. For example, a user may employ his orher computing device to access a network-based retailer for the purchaseof items and services (collectively and individually referred to as“items”) such as music, books, and electronics, just to name a few.

To take advantage of this growing marketplace, sellers frequently electto sell items through network-based retailers. For example, abook-seller may elect to sell books through a network-based retailerwhich offers books for sale. Accordingly, a seller may record someinformation regarding items they wish to offer for sale in an electronicform, such as a written description. This recorded item information maybe provided to the network-based retailer to enable the item to beoffered for sale by the network-based retailer.

Such a system may be problematic, however. Sellers may need to identifyone or more categories into which their item(s) falls before they may beoffered for sale. However, a network-based retailer may have manypossible categories into which an item may possibly be categorized.Furthermore, different network-based services may categorize items intodifferent categories. As a result, it may be difficult for a seller toidentify an appropriate category for categorizing their item.

Furthermore, network-based retailers receiving item informationsubmissions from a seller are faced with a difficult choice. Theretailer may choose to accept seller submissions as they are received,with the possibility that the seller submissions may be mis-categorized.Alternatively, network-based services may revise seller submissions,which is a costly and time-consuming activity. Thus, categorizationaccuracy may be compromised if the retailer takes no action, while,categorization costs may be significantly increased if the retailerrevises seller submissions.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing aspects and many of the attendant advantages will becomemore readily appreciated as the same become better understood byreference to the following detailed description, when taken inconjunction with the accompanying drawings, wherein:

FIG. 1 is a block diagram depicting an illustrative operatingenvironment in which a categorization service generates categoryrecommendations for items of interest to a user;

FIG. 2 is a block diagram of the operating environment of FIG. 1,illustrating the categorization service providing a user interface to auser computing device for submission of item information in response toa request from the user computing device;

FIG. 3 is an illustrative user interface for display on the usercomputing device for enabling a user to submit item information to thecategorization service;

FIG. 4A is a block diagram of the operating environment of FIG. 1,illustrating submission of item information by the user computing deviceto the categorization service;

FIG. 4B is a block diagram of the operating environment of FIG. 1illustrating the categorization service returning recommended categoriesto the user computing device in response to the received iteminformation;

FIG. 4C is a block diagram of the operating environment of FIG. 1,illustrating the categorization service automatically selecting one ormore recommended categories as item categories for assignment to an itemof interest;

FIG. 5 is an illustrative user interface for display on the usercomputing device for enabling a user to review recommended categoriesfor the item of interests, assign at least one category from therecommended categories to the items of interest, and update the iteminformation concerning the items of interest to include the assignedcategory; and

FIG. 6 is a block diagram of the operating environment of FIG. 1,illustrating a network-based service submitting a request to thecategorization service to generate a category vector for item categoriesof interest based upon submitted item information associated with theitem categories.

DETAILED DESCRIPTION

Generally described, embodiments of the present disclosure relate toautomatically categorizing items of interest to user (e.g., a seller ofthe item, such a manufacturer, wholesaler, or retailer) based uponassociated item information. The items of interest may be categorized inaccordance with item categories maintained by a network-based service(e.g., a website).

In this regard, a categorization service is described that categorizesthe items of interest on behalf of the user. For example, a useremploying a user computing device may possess an item that they wish tooffer for sale using the network-based service. The item may be anythingcapable of being offered for sale, for example, any good, service, orinformation. Accordingly, the network-based service may includenetwork-based retailers such as those which sell items for purchase tothe customer, network-based sources of entertainment and/or information(e.g., network-based encyclopedias, media sharing, etc), network-basedsocial networking services which enable users to share content with oneanother, and the like

As will be described in more detail below, in certain embodiments, theuser may prepare an electronic description of one or more items (e.g., afile including at least a written description) and submit the iteminformation using a user composing device to a categorization servicefor categorization. In alternative embodiments, the item information maybe retrieved from another source, rather than prepared by the user.

Upon receipt of the item information, the categorization serviceanalyzes the item information and compares the item information to itemcategories descriptions representing item categories of a selectednetwork-based server in order to determine category recommendations forthe items of interest represented by the item information. Thecategorization service may receive the item information directly fromthe user computing device or via the network-based service. For example,the categorization service may generate a mathematical description ofthe item information and compare this to a mathematical description ofthe item category descriptions.

Based upon these mathematical descriptions, the degree of similaritybetween the item information and item category descriptions may beestablished. Categories having item category descriptions that aredetermined to be sufficiently similar to the submitted item informationmay be determined to be category recommendations. Categories having itemcategory descriptions that are determined to lack sufficient similaritywith the item information may be ignored as category recommendations.

These category recommendations may be further employed to assign one ormore categories to the item of interest. In one embodiment, the categoryrecommendations may be provided to the user computing device for displayto the user in a user interface that enables the user to assign an itemcategory selected from the category recommendations to an item ofinterest. In alternative embodiments, one or more of the categoryrecommendations may be automatically assigned to the item of interest.For example, a selected number of category recommendations having thehighest degree of similarity (e.g., top three, top five, and the like)may be assigned as categories for the item of interest.

As the categorization service employs mathematical representations ofthe item information and item category descriptions, recommendedcategories in accordance with item categories maintained by thenetwork-based service may be generated automatically, without laborintensive manual effort. Furthermore, by enabling assignment of itemcategories from the recommended item categories, the risk ofmis-categorizing a target item is minimized. For example, in one aspect,because the user (e.g., seller) submitting the item to thecategorization service may be the most knowledgeable party concerningthe item, the user may be in the best position to select fromrecommended categories in categorizing the item. Alternatively,automatically selecting categories from category recommendations havingthe highest degree of similarity provides a high degree of confidence inthe accuracy of the assigned categories. As an additional benefit, thescope and variety of categorization that can be provided by thecategorization service is virtually unlimited.

With reference to FIG. 1, an illustrative operating environment 100 isshown including a categorization service 102 that categorizes items ofinterest submitted by a user computing device 106. For example, asdiscussed in greater detail below, the categorization service determinesitem category recommendations based upon item information regarding anitem of interest submitted by a user computing device 106. The itemcategory recommendations are further determined based upon itemcategories maintained by a network-based service 112. Therefore, thecategorized items may be employed in conjunction with the network-basedservice 112 (e.g., offered for sale).

It may be recognized that many of the components described below areoptional and that embodiments of the system 100 may or may not combinecomponents. Components need not be distinct or discrete. Components maybe reorganized in the system 100. The system 100 may be represented in asingle physical server containing all of the subsystems described belowor, alternatively, the system may be split into multiple physicalservers. For example, in certain embodiments, the categorization service102 may be housed within the network-based service. In alternativeembodiments, the categorization service 102 may comprise a stand-aloneservice. In additional embodiments, the categorization service 102 maybe housed within one or more user computing devices.

The categorization service 102 and network-based service 112 may each beembodied in a plurality of components, each executing an instance of therespective categorization service 102 or network-based service 112. Aserver or other computing component implementing the categorizationservice 102 or network-based service 112 may include a networkinterface, memory, processing unit, and computer readable medium drive,all of which may communicate which each other may way of a communicationbus. The network interface may provide connectivity over the network 110and/or other networks or computer systems. The processing unit maycommunicate to and from memory containing program instructions that theprocessing unit executes in order to operate the categorization service102 or network-based service 112. The memory generally includes RAM,ROM, and/or other persistent and auxiliary memory.

The user computing device 106 may comprise any computing device, such asa laptop or tablet computer, personal computer, personal digitalassistant (PDA), hybrid PDA/mobile phone, mobile phone, electronic bookreader, set-top box, camera, digital media player, and the like. Theuser computing device 106 may also be any of the aforementioned devicescapable of receiving or obtaining data regarding an item of interestfrom another source, such as a digital camera, a remote control, anothercomputing device, a file, etc.

In one embodiment, the user computing device 106 may communicate withthe categorization service 102 and network-based service 112 via acommunication network 110, such as the Internet or a communication link.Those skilled in the art will appreciate that the network 110 may be anywired network, wireless network or combination thereof. In addition, thenetwork 110 may be a personal area network, local area network, widearea network, cable network, satellite network, cellular telephonenetwork, or combination thereof. Protocols and components forcommunicating via the Internet or any of the other aforementioned typesof communication networks are well known to those skilled in the art ofcomputer communications and thus, need not be described in more detailherein.

In certain embodiments discussed below, the categorization service 102of FIG. 1 may generate category recommendations in response to receiptof item information regarding items of interests to the user that arereceived from the user computing device 106. It may be understood,however, that the categorization service 102 may also be employed togenerate category recommendations in response to receipt of iteminformation regarding items of interest to the network-based service112. For example, the network-based service 112 may maintain records ofprior item information submissions. It may be desirable to provide thispreviously submitted item information to the categorization service 102in order to verify and/or update the category assigned to the itemsrepresented by the previously submitted item information.

With further reference to FIG. 1, illustrative components of thecategorization service 102 for use in categorizing items described bysubmitted item information will now be addressed. In one embodiment, thecategorization service 102 includes a user interface component 116 forreceiving item information from the user computing device 106. In afurther embodiment, the categorization service 102 includes a vectorcomponent 120 for generating mathematical descriptions (e.g., vectors)of item and/or category description information. In an additionalembodiment, the categorization service 102 includes a similaritycomponent 122 for determining similarities between vectors anddetermining category recommendations on the basis of the determinedsimilarities.

Generally described, the user interface component 116 generates userinterfaces which enable a user of the user computing device 106 tointeract with the categorization service 102. For example, as describedin greater detail below, the user interface component 116 may generate afirst user interface for display by the user computing device 106 thatenables submission of item information to the categorization service 102for categorization. The item information may be submitted in formatsincluding, but not limited to, flat files and XML files. In alternativeembodiments, a user employing the user computing device 106 may directlyinput item information without storing the item information in a file.

In another example, following the generation of categoryrecommendations, the user interface component 116 may generate a seconduser interface for display by the user computing device 106. The seconduser interface may enable display of the category recommendations to theuser and enable the user, via the user computing device 106, to select acategory recommendation to be assigned to the item of interest.

The vector component 120 and similarity component 122 may be used togenerate the category recommendations. In one aspect, the vectorcomponent 120 may be used to generate vectors from the received iteminformation, referred to herein as item vectors. The item vectorscomprise a mathematical representation of at least a portion of the textinformation included within the received item information. In certainembodiments, the vector component 120 may employ a vector space model togenerate vectors. For example, each dimension of the vector maycorrespond to a separate term. Thus, if a term occurs in the iteminformation, the value of that term in the item vector is non-zero.

In certain embodiments, the value of a term in an item vector maycomprise the frequency with which the term occurs in the iteminformation. In further embodiments, the values of each of the terms ofthe item vector may be further weighted, using weighting schemesunderstood in the art. Examples of such weighting schemes may include,but are not limited to, term frequency-inverse document frequencymodeling (tf-idf).

The similarity component 122 may compare generated item vectors to atleast one category vector in order to determine item recommendations forthe item of interest represented by the item vector. In an embodiment,the category vector may comprise a mathematical representation of atleast a portion of an item category description related to an itemcategory. In another embodiment, the category vector may be generated bythe vector component 120 in a manner similar to that described above forthe item vector, with the exception that a category description employedinstead of the item information. In a further embodiment, one or morecategory vectors may be obtained from an external source. Irrespectiveof the source of the category vectors, one or more category vectors maybe stored in data store 104. In certain embodiments, the item categorydescription may correspond to item categories employed by thenetwork-based service 112 and may be retrieved from the network-basedservice 112.

The similarity component 122 determines a similarity between thegenerated item vector and at least one category vector in order todetermine category recommendations. In one embodiment, the item categoryrepresented by the category vector may be considered to be a categoryrecommendation if the similarity of the item of interest is amongst themost similar items (e.g., within the top one, within the top three,within the top five, etc.). In an alternative embodiment, the itemcategory represented by the category vector may be considered to be acategory recommendation if the similarity is greater than a thresholdvalue.

The similarity may be determined through in a number of differentoperations. In one embodiment, the similarity may comprise the deviationof the angles between the item vector and the category vector underconsideration. In another embodiment, the similarity may comprise thecosine of the angle between the item vector and the category vectorunder consideration. It may be understood that this description ofsimilarities is not exhaustive and that other methods of calculatingsimilarities known in the art may be employed within the scope of thedisclosed embodiments.

Although described above as components of the categorization service102, the user interface component 116, the vector component 120, and/orthe similarity component 122 may be discrete services or components fromthe categorization service 102. Accordingly, the categorization service102 may include one or more interface components for communication withthe user interface component 116, the vector component 120, and/or thesimilarity component 122 via the network 110.

In additional embodiments, the categorization service 102 may be housedwithin one or more user computing devices 106 and operate as discussedabove. For example, category vectors may be retrieved from data store104. In another example, category vectors may be stored by the usercomputing devices 106 and pushed to the user computing devices 106 whenupdated. Beneficially, by locally storing category vectors and pushingupdates to the user computing devices 106, the user computing devices106 may not necessarily need to be in communication with the network inorder for the categorization service 102 to categorize items of interestto the user.

FIG. 2 is a block diagram of the operating environment of FIG. 1,illustrating the categorization service 102 providing a user interfaceto a user computing device for submission of item information inresponse to a request from the user computing device. The iteminformation may be determined by the user computing device 106 and/ormay be retrieved from another source for submission to the network-basedservice 112. As noted above, the item of interest may be any good,service, or information. The item information may also take a variety offorms depending on item and/or the type of user computing device 106.

As further illustrated in FIG. 2, the user may request a user interfacefrom the network-based service 112 for submission of item informationusing the user computing device 106. For example, the request maycomprise a request for a web page containing the desired iteminformation input fields. The request may be transmitted to thenetwork-based service 112, which detects that a user interface enablingitem information to be submitted is needed to respond to the userrequest and forwards the request to the categorization service 102.

The categorization service 102, in turn, may submit the request for auser interface to the user interface component 116. In an embodiment,the user interface component 116 may generate and return a userinterface enabling submission of item information. In anotherembodiment, the user interface component may retrieve a user interfacefrom the data store 104. The user interface generated by thecategorization service 102 for item information submission may befurther transmitted to the network-based service 112 for ultimatepresentation to the user.

FIG. 3 illustrates one embodiment of a user interface 300 that isdisplayed on the user computing device 106 for submission of iteminformation. The user interface 300 includes a first window 302 whichincludes a greeting 304 and instructions 306 for use of the userinterface 300. The instructions 306 may include a step-by-step overviewof the operations involved in the item categorization process, in orderto familiarize the user with the process. Sample instructions 306 mayinclude “1. Upload your item information,” “2. Review therecommendations and select one or more categories that best fit theitem,” and “3. Save the updated item information.”

The user interface 300 may further include a second window 310 forsubmission of item information. In one aspect, the second window 310 mayinclude a field 312 for identifying a location of one or more filescontaining the item information. A user interface control 314 may befurther provided for navigating through directory structures of memorydevices (e.g., local or network storage) in communication with the usercomputing device 106 in order to identify the location of the file orfiles containing the item information. As necessary, a locale 316 of theitem information file may be selected, as necessary, in order to provideproper interpretation of the file or files containing the iteminformation.

The user interface 300 may also provide the user with an interfaceoption 320 to have recommendations selected for parent items to beinherited by their children. For example, assume that an item to becategorized is a T-shirt. Further assume that other items to becategorized are the same T-shirt, with variations such as size, color,and the like. In this example, an item categorized as “T-shirt” may beconsidered a parent, while an item categorized as “T-shirt, blue,X-Large” may be considered a child of that parent. Thus, the byselection of the interface option 320, any selections made for theparent item are also inherited by the child item.

As discussed in greater detail below, selection of the interface option320 also causes display of child items along with their parents. Whenmaking selections for the parents, the user may determine to whichchildren the parent selections are to be applied. In certainembodiments, as a default, parent selections may be applied to thosechildren that have the same category recommendations as their parent.

Once the user has provided the location of the item information and,optionally, made selections regarding the locale and inheritingrecommendations, the item information may be transmitted (e.g.,uploaded) to the categorization service 102 for generation of categoryrecommendations. If the user is satisfied with their selections, theuser may select a user interface control 322A submit the iteminformation. If, however, the user is not satisfied with theirselections, the user may select a user interface control 322B in orderto reset the user interface 300 and clear any information previouslyentered.

FIG. 4A is a block diagram of the operating environment 100 of FIG. 1,illustrating submission of item information to the categorizationservice 102 by the user computing device 106. A user, upon receiving theuser interface enabling submission of item information for an item ofinterest, may decide that they wish to categorize the item. A request tocategorize the item may be submitted, for example, by identifying one ormore files containing item information and submitting this iteminformation by selecting the user interface control 322A in userinterface 300. Upon receipt of the request, the network-based service112 submits the request to the categorization service 102, which in turngenerates category recommendations based upon the received iteminformation.

Although the request regarding categorization of the item is depicted inFIG. 4A as submitted by the user computing device 106, those skilled inthe art will appreciate that the request may be submitted from anothercomputing device utilized by the user. Upon receipt of the iteminformation, the categorization service 102 may obtain vectors in orderto facilitate the generation of category recommendations. In one aspect,an item vector may be generated from the item information using thevector component 120 of the categorization service 102. In anotheraspect, the categorization service 102 may retrieve one or more categoryvectors from the data store 104.

After the categorization service 102 obtains the item and categoryvectors, the categorization service 102 proceeds to generate categoryrecommendations and user interfaces for selection of one or morecategory recommendations for the item of interest. FIG. 4B is a blockdiagram of the operating environment 100 of FIG. 1, illustrating receiptof the item and category vectors by the categorization service 102. Inone aspect, comparisons may be made between the item and categoryvectors using the similarity component 122 of the categorization service102. Based upon the results of the similarity comparison, categoryrecommendations for the item of interest represented by the iteminformation may be identified.

In another aspect, the user interface component 116 of thecategorization service 102 may provide a user interface enabling reviewand assignment of one or more category recommendations to the item ofinterest. In an embodiment, the user interface component 116 maygenerate such a user interface. In another embodiment, the userinterface component may retrieve such a user interface from the datastore 104. The user interface generated by the categorization service102 for category recommendation review and submission may be furthertransmitted to the network-based service 112 for ultimate presentationto the user.

As further illustrated in FIG. 4B, the user may review the categoryrecommendations displayed in the user interface and assign an itemcategory to the item of interest from the category recommendations. Theitem information may be further updated to reflect the assigned itemcategory. Once the item information is updated, the updated iteminformation may be transmitted to the network-based service for storagein data store 114.

FIG. 4C is a block diagram of the operating environment 100 of FIG. 1,illustrating an embodiment of the categorization service 102 whichautomatically selects one or more recommended categories as itemcategories for assignment to an item of interest. As discussed above,the item and category vectors may be received by the categorizationservice 102 and comparisons may be made between the item and categoryvectors using the similarity component 122 of the categorization service102 to identify category recommendations for the item of interest. Inone embodiment, the categorization service 102 may assign at least oneof a selected number of the most similar category recommendations (e.g.,top one, top three, top five, etc.) as item categories for the item ofinterest. The item information may be further updated to reflect the oneor more assigned item categories. Once the item information is updated,the updated item information may be transmitted to the network-basedservice 112 for storage in the data store 114.

FIG. 5 illustrates one embodiment of a user interface 500, includingcategory recommendations that are displayed on the user computing device106. The user interface 500 includes an instruction frame 502, itemframe 504, recommended categories frame 506, and children frame 510.

The instruction frame 502 may provide the user with instructions foremploying the user interface 500. For example, as illustrated in FIG. 5,the instruction frame 502 indicates that the user should reviewcategorization recommendations for the listed items and identify one ormore category recommendations which appear to most closely match or fitthe item. The user is further instructed to submit their selections whenfinished.

The item frame 504 lists the items which are identified within thesubmitted item information by the categorization service 102. The itemframe 504 further lists a description of the identified item. The itemdescription may include any information which is deemed pertinent to thecharacteristics of the item.

In certain embodiments, the categorization service may employ programmedlogic in order to identify the items of interest listed within the iteminformation. In one aspect, the items and item descriptions may beidentified by searching for selected fields within the item information,such as “title,” “item name,” “item description,” and the like. Inanother aspect, the categorization service 102 may identify items anditem descriptions by searching for terms that are likely to be relatedto an item or item description. As illustrated in FIG. 5, an itementitled, “Henri Lloyd Paul sock set” is identified. An item descriptionis also provided, which indicates the sock set is a gift box. The itemdescription further indicates the pattern of the socks contained in thegift box, as well as the location of a brand motif and that the gift boxis a feature presentation box.

The recommended categories frame 506 may list the categoryrecommendations which are determined by the categorization service forthe item. The category recommendations 506 may be further subdivided,for example, into current category 506A, recommended categories 506B,and other recommended categories 506C.

The current category 506A reflects a current value of category which isassigned to the item. In one embodiment, the current category 506A maybe read from a “category” field of the item information. For example,the current category 506A may reflect a category which the user hasselected for the item and entered into the item information. In certainembodiments, if the user has disclosed a category recommendation for theitem of interest within the item information (i.e., an embedded categoryrecommendation), this category recommendation may be selected bydefault. Absent the recitation of a category recommendation within theitem information, the current category 506A may indicate “NoRecommendation.”

In another example, the current category 506A may reflect a categoryassignment for the item which was previously made by submission of theitem information for categorization. If new category recommendationsbecome available, it may be advantageous for an item to be resubmittedto the categorization service to verify that a previously assignedcategory remains correct.

The category recommendations 506B reflect category recommendations whichhave been determined for the item based upon the item informationsubmitted to the categorization service 102. For example, a selectednumber of category recommendations (e.g., 3, 5, 10, and the like) may bedisplayed to the user in the user interface 500. The displayed categoryrecommendations may further reflect the item categories which have beendetermined to be the most similar to the item information. In thismanner, only the categories most likely to reflect the item arerecommended to the user. Continuing the example begun above, for the“Henri Lloyd Paul Sock Set,” a selected number of categoryrecommendations are displayed, such as “Apparel/Socks & Hosiery/Socks,”“Apparel/Bags & Accessories/Ties,” and “Apparel/Swimwear/Swim Shorts.”

The user interface 500 further provides other recommendations 506C forconsideration by the user. The other recommendations 506C reflectrecommended categories which are identified by the categorizationservice but which do not fall within the most similar categoryrecommendations displayed within the category recommendations. The usermay choose to review the other recommendations 506C, for example, if theuser finds the category recommendations 506B to be unsatisfactory.

As discussed above, the user interface 300 provides the user with theoption to apply recommendations assigned to parent items to child items.The children frame 510 presents the children identified for the itemdisplayed in the item frame 504. In certain embodiments, if theinterface option 320 is not selected in the user interface 300, then thechildren frame 510 may be omitted from user interface 500. Continuingthe example begun above, the item “Henri Lloyd Paul Sock Set” isidentified to have children “Henry Lloyd Paul Sock Set Navy One Size”and “Henry Lloyd Paul Sock Set Charcoal One Size.” For each child item,the user may choose an interface option 512. By selection of theinterface option 512, the child item may inherit the assigned categoryof the parent item under consideration.

The user interface 500 further comprises user interface controls 516A,516B. When the user has completed reviewing the recommended categoriesand selected a category for assignment to the item of interest, the usermay select user interface control 516A. With selection of user interfacecontrol 516A, the item information may be updated with the assigned itemcategory. The updated item information may be further transmitted to thenetwork-based service 112 for storage. If, however, the user is notsatisfied with their selections, the user may select a user interfacecontrol 516B in order to reset any selections made in user interface500.

In further embodiments, the user may not select any of the categoryrecommendations. For example, the user may wish to consider therecommended categories in greater detail and, therefore, defers theirselection. The item information may be updated to reflect this choicewith a null value. The item information may be further provided to thecategorization service 102 at a later time to continue thecategorization process and assign one or more categories to the item ofinterest, as discussed above.

The user interface 500 has illustrated and described for the assignmentof a category to a single item. It may be understood, however, that theitem information may comprise information regarding many items.Therefore, the user interface may display multiple items, and theirrespective recommended categories and children, for review and selectionby the user without limit.

FIG. 6 is a block diagram of the operating environment of FIG. 1,illustrating the generation of category vectors by the categorizationservice 102. As discussed above, in certain embodiments, thecategorization service 102 may be operative to generate and storecategory vectors pertaining to item categories maintained by thenetwork-based service 112. Such category vectors may be established inadvance of or concurrently with the item vectors so as to facilitate thegeneration of category recommendations for a category of interest.

As illustrated in FIG. 6, the network-based service 112 may requestselected categories and associated category information from the datastore 114. This information may then be transmitted to thecategorization service 102 for the determination of category vectors.The category vector may be generated from the category information usingthe vector component 120 of the categorization service 102, as discussedabove. The generated category vector may subsequently be stored in thedata store 104 for later retrieval and use.

All of the processes described herein may be embodied in, and fullyautomated via, software code modules executed by one or more generalpurpose computers or processors. The code modules may be stored in anytype of computer-readable medium or other computer storage device. Someor all the methods may alternatively be embodied in specialized computerhardware. In addition, the components referred to herein may beimplemented in hardware, software, firmware or a combination thereof.

Conditional language such as, among others, “can,” “could,” “might” or“may,” unless specifically stated otherwise, are otherwise understoodwithin the context as used in general to convey that certain embodimentsinclude, while other embodiments do not include, certain features,elements and/or steps. Thus, such conditional language is not generallyintended to imply that features, elements and/or steps are in any wayrequired for one or more embodiments or that one or more embodimentsnecessarily include logic for deciding, with or without user input orprompting, whether these features, elements and/or steps are included orare to be performed in any particular embodiment.

Any process descriptions, elements or blocks in the flow diagramsdescribed herein and/or depicted in the attached figures should beunderstood as potentially representing modules, segments, or portions ofcode which include one or more executable instructions for implementingspecific logical functions or elements in the process. Alternateimplementations are included within the scope of the embodimentsdescribed herein in which elements or functions may be deleted, executedout of order from that shown, or discussed, including substantiallyconcurrently or in reverse order, depending on the functionalityinvolved as would be understood by those skilled in the art.

It should be emphasized that many variations and modifications may bemade to the above-described embodiments, the elements of which are to beunderstood as being among other acceptable examples. All suchmodifications and variations are intended to be included herein withinthe scope of this disclosure and protected by the following claims.

What is claimed is:
 1. A system for categorizing items, the systemcomprising: a data store that stores item information related to a firstplurality of items offered for sale using a network-based service; and acomputing device having one or more processors, wherein the computingdevice is configured to operate the network-based service and is incommunication with the data store, and wherein the network-based serviceis operative to: receive a request for a category recommendation for anitem of the first plurality of items, the request including first iteminformation associated with the item; and submit the first iteminformation to a categorization service, wherein the categorizationservice is operative to: generate an item vector from the first iteminformation according to a vector space model; compare the item vectorto at least one category vector, wherein the at least one categoryvector comprises a representation of at least a portion of a textualdescription of an item category according to the vector space model,wherein the item category is maintained by the network-based service andassociated with a second plurality of items; determine the categoryrecommendation to be the item category when a deviation of an anglebetween the item vector and the at least one category vector is lessthan a threshold value; and update the first item information to includethe item category.
 2. The system of claim 1, wherein the categorizationservice is further operative to transmit the updated first iteminformation to the network-based service.
 3. The system of claim 2,wherein the network-based service is further operative to store theupdated first item information in the data store.
 4. The system of claim1, wherein the first item information comprises at least one of a flatfile, an XML file, or information directly input by a user.
 5. Thesystem of claim 1, wherein a value of a term in the item vector isdetermined based on a frequency with which the term occurs in the firstitem information and a term frequency-inverse document frequency of theterm.
 6. A system for categorizing items of interest, the systemcomprising: a data store adapted to maintain one or more descriptionsfor one or more item categories, wherein each item of a plurality ofitems offered for sale using a network-based service is associated withat least one of the one or more item categories; and a computing devicehaving one or more processors, wherein the computing device is adaptedto operate a categorization service and is in communication with thedata store, and wherein the categorization service is operative to:generate item information associated with a first item of the pluralityof items; compare the item information to a first description in the oneor more descriptions maintained in the data store; and determine atleast one category recommendation to be a first item category based on asimilarity of the item information and the first description, whereinthe first description is a textual description of the first itemcategory; and assign the first item category to the first item, whereinthe item information is represented as an item vector according to avector space model and a category vector according to the vector spacemodel comprises a representation of at least a portion of the firstdescription, and wherein the at least one category recommendation isautomatically determined to be the first item category if a deviation ofan angle between the item vector and the category vector is less than athreshold value.
 7. The system of claim 6, wherein the categorizationservice is further operative to determine at least one categoryrecommendation to be a second item category based on a similarity of theitem information and a second description in the one or moredescriptions maintained in the data store, wherein the seconddescription is a description of the second item category.
 8. The systemof claim 7, wherein the categorization service is operative to assignthe first item category to the first item by automatically selecting thefirst item category from the at least one category recommendation. 9.The system of claim 7, wherein the categorization service is operativeto assign the first item category to the first item based on a selectionof the first item category by a human reviewer from the at least onecategory recommendation.
 10. The system of claim 9, wherein thecategorization service is further operative to provide the at least onecategory recommendation to a computing device having one or moreprocessors, wherein the computing device is operative to: present the atleast one category recommendation to the human reviewer; and receive aselection by the human reviewer of the first item category.
 11. Thesystem of claim 6, wherein the categorization service is furtheroperative to update the item information to include the first itemcategory.
 12. The system of claim 11, wherein the categorization serviceis further operative to transmit the updated item information to acomputing device in communication with another data store.
 13. Thesystem of claim 6, wherein the item information comprises at least oneof an item title and an item description.
 14. The system of claim 6,wherein the item information comprises at least one of a flat file, anXML file, or information directly input from a user.
 15. The system ofclaim 6, wherein a value of a term in the item vector is determinedbased on a frequency with which the term occurs in the item informationand a term frequency-inverse document frequency of the term.
 16. Acomputer-implemented method for categorizing, on behalf of a user, oneor more items of a plurality of items in item categories maintained by anetwork-based service, the method comprising: under control of one ormore computer systems: comparing item information with at least onedescription for a first item category in the item categories maintainedby the network-based service to determine a similarity between the iteminformation and the at least one description, wherein the at least onedescription is a textual description of the first item category, whereinthe item information is related to a first item in the plurality ofitems, wherein the first item is an item offered for sale using thenetwork-based service, and wherein the first item category is associatedwith at least one item in the plurality of items; automaticallydetermining the first item category to be at least one categoryrecommendation for the first item based on the similarity between theitem information and at least one description; enabling selection of thefirst item category for assignment to the first item, wherein the iteminformation is represented as an item vector according to a vector spacemodel and a category vector according to the vector space modelcomprises a representation of at least a portion of the at least onedescription, and wherein the first item category is automaticallydetermined to be the at least one category recommendation if a deviationof an angle between the item vector and the category vector is less thana threshold value.
 17. The computer-implemented method of claim 16,further comprising comparing the item information with at least onesecond description for a second item category in the item categoriesmaintained by the network-based service to determine a similaritybetween the item information and the at least one second description;and automatically determining the second item category to be at leastone category recommendation for the first item based upon the similaritybetween the item information and at least one second description. 18.The computer-implemented method of claim 17, wherein enabling selectionof the first item category comprises enabling automatic selection of thefirst item category from the at least one category recommendation. 19.The computer-implemented method of claim 17, wherein enabling selectionof the first item category comprises enabling selection of the firstitem category from the at least one category recommendation by a humanreviewer.
 20. The computer-implemented method of claim 19, whereinenabling selection of the first item category by the human reviewercomprises: generating a user interface that enables a human reviewer toselect the first item category from the at least one categoryrecommendation; and transmitting the user interface and the at least onecategory recommendation to another computing device for display to thehuman reviewer.
 21. The computer-implemented method of claim 16, furthercomprising updating the item information to include the first itemcategory.
 22. The computer-implemented method of claim 21, furthercomprising transmitting the updated item information to a computingdevice in communication with a data store.
 23. The computer-implementedmethod of claim 16, wherein the item information comprises at least oneof an item title and an item description.
 24. The computer-implementedmethod of claim 16, wherein the item information comprises at least oneof a flat file, an XML file, or information directly input by the user.25. The computer-implemented method of claim 16, wherein a value of aterm in the item vector is determined based on a frequency with whichthe term occurs in the item information and a term frequency-inversedocument frequency of the term.
 26. A non-transitory computer-readablemedium having encoded thereon instructions, wherein the instructions,when executed by a computing apparatus, cause the computing apparatusto: generate a first user interface for receiving, from a user, iteminformation regarding at least one item of interest to the user, whereinthe item of interest is an item offered for sale using a network-basedservice; and automatically determine at least one categoryrecommendation from vector representations of the item information andat least one description for an item category maintained by thenetwork-based service, wherein the at least one description is a textualdescription of the first item category, wherein the item category isassociated with a plurality of items and is determined to be a categoryrecommendation if a deviation of an angle between the vectorrepresentations of the item information and the at least one descriptionis less than a threshold value, wherein the item information isrepresented as an item vector according to a vector space model and acategory vector according to the vector space model comprises arepresentation of at least a portion of the at least one description.27. The non-transitory computer-readable medium of claim 26, wherein theitem information comprises at least one of an item title and an itemdescription.
 28. The non-transitory computer-readable medium of claim26, wherein the item information comprises at least one of a flat file,an XML file, or information directly input by a user.
 29. Thenon-transitory computer-readable medium of claim 26, wherein a value ofa term in the item vector is determined based on a frequency with whichthe term occurs in the item information and a term frequency-inversedocument frequency of the term.